Indirect visual odometry with a light-field camera
Year: 2025
Type: article
Abstract: Visual odometry is the technique of determining a robot’s pose by analyzing images of its surroundings as it moves. Visual odometry can be categorized into monocular when using a single camera, or stereo when using two cameras or more. In this study, we investigate the use of light-field camera for visual odometry. Capitalizing on the distinctive capability of a light-field camera to record both the intensity and the direction of light, we propose an indirect visual odometry method able to estimate the scale of the translation similarly to stereo visual odometry, but using a single camera sensor. Our visual odometry framework combines light-field imaging with conventional odometry techniques to track the camera movements, using the depth insights provided by a light-field depth estimation approach. Additionally, this method differs from state-of-the-art methods by using a simplified calibration process and a new keypoints extraction method, which makes the use of the light-field cameras easier for robotics perception. • Visual odometry is the technique of determining a robot’s pose by analyzing images of its surroundings as it moves. • Visual odometry can be categorized into monocular when using a single camera, or stereo when using two cameras in a stereo setup. • Light-field cameras are cameras able to record both the intensity and the direction of light. • An indirect visual odometry method using a light-field camera is proposed. • Estimation of the pose with the scale of the translation similarly to stereo visual odometry, but using a single camera. • The method differentiates from state-of-the-art methods by using a simplified calibration process, and a new keypoints extraction method which makes the use of the light-field cameras easier for robotics perception.
Institution: Université de Haute-Alsace
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,790
Funder: Université de Haute-Alsace
OpenAlex ID: W4415754301